Python data science cheatsheet

External Cheatsheets:

• Pandas cheatsheet

Numpy

• Numpy for matlab users

• Numpy Array to list

  np.array.tolist()

• Initializing a matrix

  # initialzing a matrix
  a = np.zeros(shape=(3, 2))
  a = np.empty(shape=(3, 2)) #initializes with random values
  a = np.full(shape=(3,2), np.nan)

• Boolean array or matrix

    a = np.full((m,n), True)
    b = np.full((m,n), False)

• np.newaxis¹

• string array with numpy²

  my_array = numpy.empty([1, 2], dtype="S10")
  # S10 -> 10 characters
  # Add S_num to preallocate number of strings

Pandas

• Data import

data = pd.read_csv(os.path.join(root_folder, filename), sep=‘\t’, skiprows=1, header=None, names=[‘col1’,‘col2’])

to reset indexes (and drop it)

data.reset_index(drop=True, inplace=True)
```

• Iteration<sup>3</sup>

  # iterating through rows (NOT RECOMMENDED)
  for i, row in df.iterrows():
  	print(row)
  # iterating through index (probably not recommended)
  for i in df.index:
  	print(i)

• Nested dictionary to dataframe (from_dict)

  d = dict{1:{'a':0, 'b':1}, 2:{'a': 1, 'b':10}}
  df = pd.DataFrame.from_dict(d ,orient='index')

• Adding (extra) named indexes (rows) and sorting column based on named indexes

  df.loc["mean"] = df.mean()
  df = df.sort_values("mean", axis=1, ascending=False)

Scipy

Interpolation

• https://docs.scipy.org/doc/scipy/tutorial/interpolate/smoothing_splines.html
• https://numpy.org/devdocs/reference/generated/numpy.interp.html#numpy.interp

Integration

• Simpson’s rule: https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.simpson.html

JAX

• Key concepts
• How to think in JAX
• In place operations in JAX

PyMC

Intro to PyMC

Setup

conda install numpy pandas scipy scikit-learn matplotlib seaborn dill
# optional
conda install ipykernel ipywidgets # for vscode + jupyter

Footnotes

1. https://stackoverflow.com/questions/29241056/how-do-i-use-np-newaxis ↩

2. https://stackoverflow.com/questions/13717554/weird-behaviour-initializing-a-numpy-array-of-string-data ↩

3. https://stackoverflow.com/questions/16476924/how-can-i-iterate-over-rows-in-a-pandas-dataframe ↩